Triple

T30733366
Position Surface form Disambiguated ID Type / Status
Subject Folsom Street E782478 entity
Predicate hosts P186 FINISHED
Object Folsom Street Fair
Folsom Street Fair is a large annual BDSM and leather subculture street festival held in San Francisco, known as one of the world’s biggest kink and fetish events.
 E1929128 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Folsom Street Fair | Statement: [Folsom Street, hosts, Folsom Street Fair]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Folsom Street Fair
Triple: [Folsom Street, hosts, Folsom Street Fair]
Generated description
Folsom Street Fair is a large annual BDSM and leather subculture street festival held in San Francisco, known as one of the world’s biggest kink and fetish events.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f224ad9f9c81908e02a79ae0001137 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68ee54d1c8190a4c020394f7fb19a completed May 2, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a289913cec48190963e940be54121e1 completed June 9, 2026, 10:52 p.m.
NEDg Description generation batch_6a289af04cc08190a45004a2c7d2e6b7 completed June 9, 2026, 11 p.m.
NED2 Entity disambiguation (via description) batch_6a289ba3fe2881909d2b7db74cf7aa82 completed June 9, 2026, 11:03 p.m.
Created at: April 29, 2026, 8:37 p.m.